Miroslav Krstic

This monograph presents new constructive design methods for boundary stabilization and boundary estimation for several classes of benchmark problems in flow control, with potential applications to turbulence control, weather forecasting, and plasma control. One of the main features of the book is a unique "backstepping" approach to parabolic partial differential equations, which yields not only the stabilization of the flow, but also the explicit solvability of the closed-loop system. The work is an excellent reference for a broad, interdisciplinary engineering and mathematics audience: control theorists, fluid mechanicists, mechanical engineers, aerospace engineers, chemical engineers, electrical engineers, applied mathematicians, as well as research and graduate students in these fields.

An up-close look at the theory behind and application of extremum seeking Originally developed as a method of adaptive control for hard-to-model systems, extremum seeking solves some of the same problems as today’s neural network techniques, but in a more rigorous and practical way. Following the resurgence in popularity of extremum-seeking control in aerospace and automotive engineering, Real-Time Optimization by Extremum-Seeking Control presents the theoretical foundations and selected applications of this method of real-time optimization. Written by authorities in the field and pioneers in adaptive nonlinear control systems, this book presents both significant theoretic value and important practical potential. Filled with in-depth insight and expert advice, Real-Time Optimization by Extremum-Seeking Control: *Develops optimization theory from the points of dynamic feedback and adaptation *Builds a solid bridge between the classical optimization theory and modern feedback and adaptation techniques *Provides a collection of useful tools for problems in this complex area *Presents numerous applications of this powerful methodology *Demonstrates the immense potential of this methodology for future theory development and applications Real-Time Optimization by Extremum-Seeking Control is an important resource for both students and professionals in all areas of engineering–electrical, mechanical, aerospace, chemical, biomedical–and is also a valuable reference for practicing control engineers.

In the 70+ year history of control theory and engineering, few applications have stirred as much excitement as flow control. The same can probably be said for the general area of fluid mechanics with its much longer history of several centuries. This excitement is understandable and justified. Turbulence in fluid flows has been recognized as the last great unsolved problem of classical 1 physics and has driven the careers of many leading mathematicians of the 20th century.2 Likewise, control theorists have hardly ever come across a problem this challenging. The emergence of flow control as an attractive new field is owed to the break­ throughs in micro-electro-mechanical systems (MEMS) and other technologies for instrumenting fluid flows on extremely short length and time scales. The remaining missing ingredient for turning flow control into a practical tool is control algorithms with provable performance guarantees. This research mono­ graph is the first book dedicated to this problem-systematic feedback design for fluid flows.

This monograph presents the fundamentals of global stabilization and optimal control of nonlinear systems with uncertain models. It offers a unified view of deterministic disturbance attenuation, stochastic control, and adaptive control for nonlinear systems. The book addresses a large audience of researchers, students, engineers and mathematicians in the areas of robust and adaptive nonlinear control, nonlinear H... stochastic nonlinear control (including risk-sensitive), and other related areas of control an d dynamical systems theory.

Using a pedagogical style along with detailed proofs and illustrative examples, this book opens a view to the largely unexplored area of nonlinear systems with uncertainties. The focus is on adaptive nonlinear control results introduced with the new recursive design methodology--adaptive backstepping. Describes basic tools for nonadaptive backstepping design with state and output feedbacks.